BSC Six Sigma: ASQ Meeting 12 September Copyright 2006 Boston Scientific

Transcription

1 Six Sigma at Boston Scientific Tuesday September 006 Steve Czarniak

2 Session Objectives Describe the Boston Scientific Six Sigma Model Describe the Boston Scientific Six Sigma Roadmaps Identify which Minitab graphs to use to assess measurement system performance

3 Six Sigma at BSC is... 3

4 Improvement Challenges Solution Known Change in Performance Operational Defect / Variation Reduction Flow Design 4

5 BSC Six Sigma Problem Solving Roadmap 5

6 BSC Six Sigma Operational Process Improvement Roadmap Yield Control Process Improvement Process Improve Control x s Analyze Optimize x s Define Measure Identify y s (Outputs) Identify Key x s (Inputs) y = f(x) Identify Opportunity Time 6

7 DMAIC Improvement Process Define Measure Analyze Improve Control Identify Opportunity Define Project Goal Define Process Establish Boundaries Determine Customer Requirements Define Key Y Variables Develop Measures (y s) Evaluate Measurement System Determine Process Stability Determine Process Capability Determine the Improvement Approach Identify Potential x s Analyze x s Identify Key x s Determine Stability & Capability of Key x s Establish Relationships between y s & x s Establish Targets & Tolerances for Key x s Implement Mistake Proofing Develop, Select & Verify Process Improvements Control Key x s Validate Process Verify Long Term Capability Monitor y s ys Finalize the Control System Finalize Project Charter 7

8 Balloon Scrap Reduction Define: Reduce balloon scrap for major scrap code by 80% Scrap % by Reason Code Scaled Scrap Trend 70% UC L= % Individual Value Observation _ X=0.7 LC L=-.864 Stable! Scrap 50% 40% 30% 3 0% UC L=.63 Moving Ran nge MR= % 0% Cause Cause Cause 3 Cause 4 Other Scrap Code 0 LC L= Observation Measure: Length Gage R&R (ANOVA) for Min Measure Components of Variation Percent %Contribution %Study Var %Process %Tolerance Gage name: Date of study: Reported by: Tolerance: Misc: By Part 0 Gage R&R Repeat Reprod Part-to-Part R Chart by Operator Part By Operator Sample Range Sample Mean Xbar Chart by Operator UCL= R= LCL=0 Mean=0.679 UCL=0.700 LCL=0.638 Average Operator Operator*Part Interaction.5 Operator Part

9 Balloon Scrap Reduction Analyze: Designed Experiment Normal Probability Plot of the Effects (response is Scaled Length, Alpha =.05) A Effect Type Not Significant Significant Percent Factor A B C D E Name A dhesiv e Ty pe B C D E Effect Lenth's PSE = Improve / Control: Mistake Proofing only use preferred adhesive type! 60% scrap reduction! 9

10 Business Process Improvement Roadmap - DMAIC Define Measure Analyze Improve Control What are you trying to accomplish? How will you know the project has been successful? What elements in your process can be leveraged for improvement? What is your improvement? Lean and Six Sigma both use the DMAIC roadmap as a common approach for process improvement What is your plan to implement and maintain the improvement? 0

11 Business Process Improvement

12 Price Approval Process Reduce Time, Increase Consistency Define Measure Analyze Improve Control Defined goal, talked to the customers and started to understand process complexity Collected data on time and logistics for price approvals Developed detailed process maps, identified waste and non-value added steps, identified gaps between ideal and current state Developed target state, piloted tools for standardizing price approvals and automating repetitive tasks Developed control plan, implemented and monitored new process

13 Price Approval - Results 75% reduction in response time to customer 6% reduction in process steps 88% reduction in decision steps Standardized processes: consistency, accuracy Customer driven solution With BPI, our main focus was on our Customer and the requirements that they had. Without their feedback and keeping them our main focus, we would have probably come up with a totally different solution for the process of requesting and receipt of approvals Team Leader 3

14 Does this product meet spec? Lower Spec Upper Spec A: yes B: no C: maybe D: not sure - phone a friend 4

15 Measurement System Analysis: Gage R&R

16 The Basic Model The total observed variation is equal to the real process variation plus the variation due to the measurement system. observed = σ process σ + σ measurement 6

17 Effect of Measurement Variation Actual process variation - No measurement variation Frequency LSL USL Process Total observed variation 5 LSL USL - With measurement variation Frequenc cy Observed

18 Gage R & R Means of assessing the repeatability and reproducibility of a measurement system. Evaluates how much total observed variation is due to the measurement device and measurement methods 5 LSL USL Freque ency Measurement? Variation vs. Actual Process Variation Observed

19 Gage R&R Example: Graphical Output Gage R&R (ANOVA) for Measurement Gage name: Date of study : Reported by : Tolerance: Misc: 00 Components of Variation % Contribution % Study Var.00 Measurement by Part Percent Sample Range Gage R&R Repeat Reprod R Chart by Operator 3 Xbar Chart by Operator 3 Part-to-Part UCL=0.5 _ R= LCL= Part Measurement by Operator Operator Operator * Part Interaction Sam mple Mean _ UCL= X= LCL= Average Operator Part

20 Measurement System Terms Stability Accuracy Precision Resolution Bias Reproducibility Linearity Discrimination i i Repeatability Calibration 0

21 Gage R&R Example: Graphical Output At each table, identify ONE graphic that best describes each term. Gage R&R (ANOVA) for Measurement Gage name: Date of study : Reported by : Tolerance: Misc: Percent Sample Range Components of Variation 00 % Contribution.00 % Study Var Measurement by Part 0 Gage R&R Repeat Reprod Part-to-Part to Part 0.0 R Chart by Operator 3 Measurement by Operator UCL= _ R= S _ UCL= X= LCL= Sam mple Mean 0.00 LCL=0 3 Operator Xbar Chart by Operator 3 Operator * Part Interaction Average Part Operator

22 Destructive Gage R&R Reference: De Mast, Jeroen; and Trip, Albert (005). Gauge R&R Studies for Destructive Measurement. Journal of Quality Technology 37 (), pp